Jameson,
I disagree that my numbers contradict my claim. Here are my numbers
presented more succinctly:
type immutable
no update 0.14 0.04
fast update 0.62 not available
slow update 4.51 0.35
The difference I am complaining about is between 'fast update' and 'slow
update' for 'immutable'. Since fast update is not available for
'immutable', we can only guess how much improvement is possible. However,
judging from the improvement between slow and fast update for 'type', it
seems likely to me that there would also be a noticeable difference for
'immutable.'
As for llvm, I don't know what its properties and limitations are.
However, it seems to me that a more intuitive way to deal with the issue I
raise (compared to current Julia) is to deprecate the current usage of
'immutable' and instead split the two attributes into two keywords:
type A : refcounted # like current 'type'
end
type A : immutable # like current 'immutable'
end
type A : refcounted, immutable # not currently available
end
type A # i.e., neither refcounted nor immutable; not currently available.
end
On Tuesday, August 5, 2014 5:38:17 PM UTC-4, [email protected] wrote:
>
> Dear Julia users,
>
> It seems to me that Julia's distinction between a 'type' and an
> 'immutable' conflates two independent properties; the consequence of this
> conflation is a needless loss of performance. In more detail, the
> differences between a 'type' struct and 'immutable' struct in Julia are:
>
> 1. Assignment of 'type' struct copies a pointer; assignment of an
> 'immutable' struct copies the data.
>
> 2. An array of type structs is an array of pointers, while an array of
> immutables is an array of data.
>
> 3. Type structs are refcounted, whereas immutables are not. (This is not
> documented; it is my conjecture.)
>
> 4. Fields in type structs can be modified, but fields in immutables cannot.
>
> Clearly #1-#3 are related concepts. As far as I can see, #4 is completely
> independent from #1-#3, and there is no obvious reason why it is forbidden
> to modify fields in immutables. There is no analogous restriction in C/C++.
>
> This conflation causes a performance hit. Consider:
>
> type floatbool
> a::Float64
> b:Bool
> end
>
> If t is of type Array{floatbool,1} and I want to update the flag b in
> t[10] to 'true', I say 't[10].b=true' (call this 'fast'update). But if
> instead of 'type floatbool' I had said 'immutable floatbool', then to set
> flag b in t[10] I need the more complex code t[10] =
> floatbool(t[10].a,true) (call this 'slow' update).
>
> To document the performance hit, I wrote five functions below. The first
> three use 'type' and either no update, fast update, or slow update; the
> last two use 'immutable' and either no update or slow update. You can see
> a HUGE hit on performance between slow and fast update for `type'; for
> immutable there would presumably also be a difference, although apparently
> smaller. (Obviously, I can't test fast update for immutable; this is the
> point of my message!)
>
> So why does Julia impose this apparently needless restriction on immutable?
>
> -- Steve Vavasis
>
>
> julia> @time testimmut.type_upd_none()
> @time testimmut.type_upd_none()
> elapsed time: 0.141462422 seconds (48445152 bytes allocated)
>
> julia> @time testimmut.type_upd_fast()
> @time testimmut.type_upd_fast()
> elapsed time: 0.618769232 seconds (48247072 bytes allocated)
>
> julia> @time testimmut.type_upd_slow()
> @time testimmut.type_upd_slow()
> elapsed time: 4.511306586 seconds (4048268640 bytes allocated)
>
> julia> @time testimmut.immut_upd_none()
> @time testimmut.immut_upd_none()
> elapsed time: 0.04480173 seconds (32229468 bytes allocated)
>
> julia> @time testimmut.immut_upd_slow()
> @time testimmut.immut_upd_slow()
> elapsed time: 0.351634871 seconds (32000096 bytes allocated)
>
> module testimmut
>
> type xytype
> x::Int
> y::Float64
> z::Float64
> summed::Bool
> end
>
> immutable xyimmut
> x::Int
> y::Float64
> z::Float64
> summed::Bool
> end
>
> myfun(x) = x * (x + 1) * (x + 2)
>
> function type_upd_none()
> n = 1000000
> a = Array(xytype, n)
> for i = 1 : n
> a[i] = xytype(div(i,2), 0.0, 0.0, false)
> end
> numtri = 100
> for tri = 1 : numtri
> sum = 0
> for i = 1 : n
> @inbounds x = a[i].x
> sum += myfun(x)
> end
> end
> end
>
>
> function type_upd_fast()
> n = 1000000
> a = Array(xytype, n)
> for i = 1 : n
> a[i] = xytype(div(i,2), 0.0, 0.0, false)
> end
> numtri = 100
> for tri = 1 : numtri
> sum = 0
> for i = 1 : n
> @inbounds x = a[i].x
> sum += myfun(x)
> @inbounds a[i].summed = true
> end
> end
> end
>
> function type_upd_slow()
> n = 1000000
> a = Array(xytype, n)
> for i = 1 : n
> a[i] = xytype(div(i,2), 0.0, 0.0, false)
> end
> numtri = 100
> for tri = 1 : numtri
> sum = 0
> for i = 1 : n
> @inbounds x = a[i].x
> sum += myfun(x)
> @inbounds a[i] = xytype(a[i].x, a[i].y, a[i].z, true)
> end
> end
> end
>
>
> function immut_upd_none()
> n = 1000000
> a = Array(xyimmut, n)
> for i = 1 : n
> a[i] = xyimmut(div(i,2), 0.0, 0.0, false)
> end
> numtri = 100
> for tri = 1 : numtri
> sum = 0
> for i = 1 : n
> @inbounds x = a[i].x
> sum += myfun(x)
> end
> end
> end
>
> function immut_upd_slow()
> n = 1000000
> a = Array(xyimmut, n)
> for i = 1 : n
> a[i] = xyimmut(div(i,2), 0.0, 0.0, false)
> end
> numtri = 100
> for tri = 1 : numtri
> sum = 0
> for i = 1 : n
> @inbounds x = a[i].x
> sum += myfun(x)
> @inbounds a[i] = xyimmut(a[i].x, a[i].y, a[i].z, true)
> end
> end
> end
>
> end
>
>
>
>
